Annual Applied Complexity Network and Board of Trustees Symposium: The Complexity of Intelligence - New Science for Hybrid Intelligence (video)

Symposium

All day

November 3, 2017– November 4, 2017

This event is by invitation only.

We are living in an age obsessed with intelligent systems. All walks of life are being transformed by innovations in machine learning, by software platforms that amplify human ability (from Mathematica to LinkedIn), improving online educational opportunities (MOOCs), and unprecedented access to the collective insights of globally dispersed communities of researchers and data sets (Wikipedia, Stack Exchange). These facts are changing both science and business.

This meeting seeks to explore the evolving landscape of intelligent systems with a focus on hybrid natural and artificial intelligence. These are hybrids in which induction, encoding, storage, deduction, and strategy are all shared across organically and culturally evolved intelligent systems (from spider webs to the WWW). In hybrid systems, individual reason is amplified by collectives where these collectives are made up by individuals and intelligent machines. These systems span defense systems, health care systems, and financial markets.

In this meeting we treat intelligent systems as complex systems exploring the connections and dependencies linking multiple intelligent systems into hybrids, exploring the new ideas and tools required to understand and control these emerging systems.

Below are some of the questions that we seek to address.

1. What will happen to efforts at human understanding when computing platforms equal or outperform our best mechanistic sciences? What will this mean for the structure of knowledge and institutions that create, curate, and depend on reliable knowledge?

2. What are the limits of insight and prediction associated with computational science? How will the scientific revolution of the 17th century be combined with the revolution of the 21st century? Combining the best of fundamental theory with the best of machine prediction to produce robust general-purpose intelligent systems.

3. Can we map out those areas of activity, from engineering, the economy, health care, and national defense, where computational and data science will continue to be transformative and how should we integrate these into enduring systems of human thought and value?

4. What might society look like when human strategy and reason is outsourced to global algorithms? Specifically, what changes might we see in the areas of education, sovereignty, finance, and resource scarcity?

5. How should we think about the differences and commonalities among natural perceptual, motor, and “analytical” intelligence? Why has there been so much emphasis on the pathological examples of Chess and Go and so little on the natural examples movement, emotion, and sociality, which have a greater impact on life and wellbeing?

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